Publication Date
In 2025 | 2 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 4 |
Since 2016 (last 10 years) | 9 |
Since 2006 (last 20 years) | 10 |
Descriptor
Classification | 14 |
Data Analysis | 14 |
Elementary School Students | 14 |
Student Behavior | 5 |
Data Collection | 4 |
Age Differences | 3 |
Grade 5 | 3 |
Problem Solving | 3 |
Academic Achievement | 2 |
Arithmetic | 2 |
Behavior Patterns | 2 |
More ▼ |
Source
Author
Publication Type
Reports - Research | 8 |
Journal Articles | 7 |
Reports - Descriptive | 2 |
Speeches/Meeting Papers | 2 |
Numerical/Quantitative Data | 1 |
Tests/Questionnaires | 1 |
Education Level
Elementary Education | 10 |
Middle Schools | 5 |
Intermediate Grades | 4 |
Grade 5 | 3 |
Secondary Education | 3 |
Grade 6 | 2 |
Junior High Schools | 2 |
Early Childhood Education | 1 |
Grade 2 | 1 |
Grade 4 | 1 |
Grade 7 | 1 |
More ▼ |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Child Behavior Checklist | 1 |
National Assessment of… | 1 |
What Works Clearinghouse Rating
Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
Poole, Frederick J.; Clarke-Midura, Jody – Language Learning & Technology, 2023
Research involving digital games and language learning is rapidly growing. One advantage of using digital games to support language learning is the ability to collect data on students learning in real time. In this study, we use educational data mining methods to explore the relationship between in-game data and elementary students' Chinese…
Descriptors: Computer Games, Second Language Learning, Second Language Instruction, Data Analysis
Oregon Department of Education, 2016
The Oregon Department of Education (ODE) partnered with 15 elementary schools to obtain and analyze student-level daily attendance records for 6,390 students. Schools ranged in size from just over 100 students to more than 600 students. Geographic locations also varied with 4 schools located in a city, 4 in a suburb, 4 in a town, and 3 in a rural…
Descriptors: Attendance Patterns, Elementary School Students, Scheduling, Holidays
Cui, Yang; Chu, Man-Wai; Chen, Fu – Journal of Educational Data Mining, 2019
Digital game-based assessments generate student process data that is much more difficult to analyze than traditional assessments. The formative nature of game-based assessments permits students, through applying and practicing the targeted knowledge and skills during gameplay, to gain experiences, receive immediate feedback, and as a result,…
Descriptors: Educational Games, Student Evaluation, Data Analysis, Bayesian Statistics
Maf'ulah, Syarifatul; Juniati, Dwi; Siswono, Tatag Yuli Eko – Educational Research and Reviews, 2016
The fact that there is no much study on reversibility is one of reason this study was conducted. Others, the importance of reversibility is also being researcher's motivation for focusing pupils' reversibility. On the other hand, the concern on pupils' reversibility is a major concern. The objective of this research is to identify errors done by…
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Error Patterns
Yeung, Cheuk Yu; Shum, Kam Hong; Hui, Lucas Chi Kwong; Chu, Samuel Kai Wah; Chan, Tsing Yun; Kuo, Yung Nin; Ng, Yee Ling – International Association for Development of the Information Society, 2017
Attributes of teaching and learning contexts provide rich information about how students participate in learning activities. By tracking and analyzing snapshots of these attributes captured continuously throughout the duration of the learning activities, teachers can identify individual students who need special attention and apply different…
Descriptors: Mathematics Instruction, Educational Technology, Technology Uses in Education, Handheld Devices
Ng, Kelvin H. R.; Hartman, Kevin; Liu, Kai; Khong, Andy W. H. – International Educational Data Mining Society, 2016
During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/division. The learning environment first modeled and then supported the use of a scripted series…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Arithmetic, Problem Solving
Isenberg, Eric; Teh, Bing-ru; Walsh, Elias – Journal of Research on Educational Effectiveness, 2015
Researchers often presume that it is better to use administrative data from grades 4 and 5 than data from grades 6 through 8 for conducting research on teacher effectiveness that uses value-added models because (1) elementary school teachers teach all subjects to their students in self-contained classrooms and (2) classrooms are more homogenous at…
Descriptors: Teacher Effectiveness, Elementary School Students, Elementary School Teachers, Academic Achievement

White, Kathleen M. – Child Development, 1971
Descriptors: Ability Identification, Age Differences, Classification, Cognitive Ability

Kroes, William H.; Libby, William L., Jr. – Journal of Genetic Psychology, 1973
Study compared the relative power of the Taxonomic, Semantic Differential, and Sense Impression categories in the recall behavior of children. (Authors)
Descriptors: Age Differences, Classification, Cluster Grouping, Data Analysis
Smith, Calvin M., Jr. – 1972
A study to explore the effectiveness of the Columbus, Ohio, Public School Systems' compensatory education program on the reading and mathematics achievement of pupils in fourth, fifth, and sixth grades was conducted. Intent of the study was (1) To study the differential achievement reached by all eligible pupils; and (2) To analyze a selected…
Descriptors: Academic Achievement, Classification, Comparative Analysis, Compensatory Education
Koskenniemi, Matti; Holopainen, Pentti – 1973
An attempt to record what pupils think and feel during the instructional process is the basis of this investigation of pupils' goal-related behavior. Two experiments are described that analyze what fourth grade pupils can tell about their activities during the instructional period when they are aided by an immediate videotape replay. These…
Descriptors: Behavior Patterns, Behavioral Science Research, Classification, Classroom Environment